Superlog is an open-source, Y Combinator-backed observability tool built for startups and lean engineering teams. A wizard scans your repo, instruments it with OpenTelemetry, and re-runs daily to keep logs, alerts, and dashboards in sync with your code. When something breaks, an AI agent groups noisy errors into a single incident, investigates with full context, and posts a merge-ready pull request in Slack. Your telemetry stays vendor-neutral, so you keep every log, trace, and metric even if you leave.

• Automated OpenTelemetry Instrumentation: Run a single command and Superlog scans your repo, finds your services, and adds request spans, queue metrics, and structured error logs. It re-runs daily to keep instrumentation current as you ship new code.
• AI-Powered Incident Grouping: Similar errors are merged into clear-cut incidents with a severity score (SEV1-3) and impact assessment, replacing a flood of duplicate alerts with concise summaries.
• Autonomous Bug-Fix PRs: When the agent identifies a SEV1 issue, it produces a tested, merge-ready pull request and delivers it straight to Slack. You can merge, ignore, or open it as a Claude Code session to tweak.
• Vendor-Neutral Telemetry: All instrumentation uses standard OpenTelemetry SDKs. You own your logs, traces, and metrics and can plug Superlog alongside Sentry, Datadog, or any other stack.
• Multi-Language Support: Dedicated instrumentation skills for Python, FastAPI, Flask, Next.js/Vercel, Expo/React Native, and LiveKit, plus fallback guidance for Go, Java, Ruby, Rust, .NET, PHP, and Elixir.
• Slack-Native Workflow: Every incident and fix flows through Slack. One PR per incident, with severity and impact upfront, so your team stays in their existing workflow.
• LLM & Upstream Cost Tracking: Automatically tracks LLM and upstream service costs by callsite, tenant, and model, giving you visibility into AI-related spend.
• Confidence-Scored Metrics: Every LLM-enhanced metric ships with a confidence score, so wrong guesses don't get amplified into false alerts.

• Zero-Config Setup: A single command instruments your entire repo with production-grade OpenTelemetry. No manual configuration or YAML wrangling required.
• Eliminates Alert Fatigue: Instead of hundreds of duplicate error notifications, you get one grouped incident with severity, impact, and a proposed fix.
• Actionable Output: Delivers tested, merge-ready PRs rather than just dashboards and alerts, which directly reduces mean time to resolution.
• No Vendor Lock-In: Built entirely on OpenTelemetry standards. You keep all your telemetry data even if you stop using Superlog.
• Works Alongside Existing Tools: Can be plugged in next to Sentry, Datadog, or Grafana without replacing your current stack.
• Open-Source and Customizable: Superlog provides open-source instrumentation skills and agents, giving teams visibility into how telemetry is collected and the flexibility to customize workflows when needed.

• Smaller Integration Ecosystem: The platform currently offers fewer integrations and community resources than long-established competitors.
• AI Fix Accuracy: The autonomous bug-fix PRs rely on LLM reasoning, which may not always produce correct patches for complex or nuanced issues, requiring human review.
• Limited Dashboard Experience: Superlog is designed to be "the observability tool you're not supposed to open," which means teams that want deep manual exploration of metrics and traces may find the interface minimal.
• Slack Dependency: The core workflow is Slack-native, which could be limiting for teams that use other communication platforms.

• Startup Engineering Teams Without DevOps: Small teams that lack dedicated SRE or DevOps headcount can get production-grade observability running in minutes. Superlog handles instrumentation, alerting, and even proposes fixes, so engineers can focus on building features instead of configuring monitoring.
• Rapid Incident Response: When a production issue surfaces at 2 AM, Superlog groups the errors, investigates root cause using logs, traces, and recent deploys, and posts a merge-ready fix to Slack. Engineers wake up to a solution instead of a wall of alerts.
• Greenfield Projects Needing Observability From Day One: New projects can add structured logging, tracing, and metrics with a single command before the first deployment, avoiding the common pattern of bolting on observability after the first outage.
• LLM-Powered Applications: Teams building AI products can track LLM costs by callsite, tenant, and model, and monitor upstream API performance alongside standard application metrics.
• Mobile App Monitoring with Expo/React Native: Mobile teams using Expo or React Native get a dedicated SDK for traces, logs, sessions, auto-instrumentation, and source map uploads, filling a gap in the mobile observability space.
• Migrating Away from Vendor Lock-In: Teams locked into proprietary observability platforms can adopt Superlog to get vendor-neutral OpenTelemetry instrumentation and gradually move their telemetry without disrupting existing workflows.